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ANALISA KINERJA BIAYA DAN WAKTU MENGGUNAKAN METODE KONSEP NILAI HASIL (EARNED VALUE CONCEPT) (Studi Kasus : Proyek Pembangunan Gedung Ruang Kelas Baru Madrasah Tsanawiyah Negeri (MTsN), Amlapura , Kabupaten Karangasem)

2022· article· id· W4386706280 on OpenAlexaff
Ida Bagus Gede Indramanik, Ni Kadek Astariani, I Wayan Sudiarsana

Bibliographic record

VenueJurnal Teknik Gradien · 2022
Typearticle
Languageid
FieldHealth Professions
TopicOccupational Health and Safety Management
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsHumanitiesPhysicsArt

Abstract

fetched live from OpenAlex

Tuntutan untuk dapat menyelesaikan proyek yang efektif dan efisien berdasarkan waktu, mutu dan biaya yang telah direncanakan memerlukan suatu pelaksanaan manajemen proyek yang baik. Proses pengendalian proyek memegang peranan yang sangat penting untuk meminimalisir kemungkinan terjadinya penyimpangan dalam pelaksanaan proyek. Pembangunan ruang kelas baru Madrasah Tsanawiyah Negeri Karangasem dipilih sebagai studi karena diawal pelaksanan proyek sudah nampak terjadi penyimpangan-penyimpangan dari sisi waktu. Teramati minggu ke-2,3 dan 4 terjadi keterlambatan dan terjadinya permasalahan menyangkut upah borongan pekerjaan. Penelitian dilakukan dalam rangka mengkaji kinerja biaya dan waktu serta untuk mengetahui perkiraan keuntungan atau kerugian proyek pada akhir penyelesaian proyek. Earned Value Concept merupakan metode yang digunakan pada studi kasus ini. Data yang digunakan RAB, time schedulle, laporan kemajuan pekerjaan dan laporan keuangan proyek. Dari hasil analisis, kinerja biaya dari proyek yang diteliti sangat baik. Hal ini terlihat dari indikator CPI yaitu 1,057 (CPI > 1) pada akhir penyelesaian proyek yang memiliki makna biaya aktual yang dikeluarkan lebih kecil dari nilai pekerjaan yang didapat. Kinerja waktu dari proyek sangat baik. Indikator yang menyatakannya yaitu didapatkannya nilai SPI yaitu 1,000 (SPI = 1 ) yang memiliki makna kinerja proyek sama dengan jadwal rencana. Baiknya kinerja biaya dan waktu dari pelaksanaan proyek mengakibatkan kontraktor mendapatkan keuntungan sebesar Rp. 144,685,050.00.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.002
Scholarly communication0.0060.005
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.047
GPT teacher head0.352
Teacher spread0.304 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations4
Published2022
Admission routes1
Has abstractyes

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